Method for monitoring the signal quality in transparent optical networks

ABSTRACT

In order to monitor the signal quality in transparent optical transmission paths, the signal is sampled asynchronously, the distribution of the sample results in recorded and a signal quality parameter is formed, in that only those flanks which are located away from the maxima of the distribution are evaluated.

BACKGROUND OF THE INVENTION

The subject matter of the application relates to a method for monitoringthe signal quality in transparent optical transmission paths, and themethod asynchronously samples the signal, determines the position of thelocal maximum a for the low logic 0 and a maximum b for a high logicstate 1, and determines a signal quality parameter Q from thedistribution.

Such a method is disclosed in DE 195 04 896.

Optical networks on the basis of high bit rate, fiber-based transmissionpaths with optical switches and, possibly, also using opticalfrequency-division multiplex represent the future transport network fortelecommunications. Already existing networks will be supported on thisnetwork, which will initially be installed as an overlay.

The further development to be expected with communications networksmakes it necessary to design the optical networks to be as transparentas possible for their users. Various levels of transparency are possiblein this case. It is thus necessary to distinguish whether a network istransparent with regard to the type of modulation, the line code, theclock frequency and/or the transmission format—that is to say, forexample, the choice between a plesiochronous or synchronous digitalhierarchy. A range of combinations are of practical importance in thiscase, with a network of maximum transparency being transparent withregard to type of modulation, line code, clock frequency andtransmission format, with the type of modulation being defined for alower level of transparency, with the freedom with regard to the linecode also being lacking in an even lower transparency level, and withlow transparency providing only freedom with regard to the transmissionformat.

The management of networks makes it necessary to monitor thetransmission quality. In synchronous digital hierarchy networks or inATM transmission networks, this function is provided by formingso-called bit interleaved parity (BIP), that is to say bit parity over ablock of user data. The result of the parity calculation is in this casealso transmitted in addition to the user data from the transmitter nodeto the receiver node where an assessment of the transmission quality andthe identification of transmission errors are possible by comparing thenewly calculated parity with the received value. However, this method isdependent on direct access to the user data being possible in eachnetwork node, which runs counter to the users' wishes for the greatestpossible transparency in the transmission paths.

Apart from monitoring the transmission quality by investigating the bitparity, it is also known for at least one channel of an opticalfrequency-division multiplex signal to be reserved for monitoringpurposes in each case. The information flows required for networkmanagement then run via this channel, with the parameters for thischannel being reliably known, and with sufficient transmission capacityfor test sequences generally being available. Although reliableinformation about the transmission quality of high-transparency networksis obtained in this way, this is dependent on the monitoring channelbeing representative of all the other transmission channels. Thehypothesis that all the channels in an optical frequency-divisionmultiplex system are affected equally by a disturbance is, however, notvalid in many cases. Particularly in optical networks, there are a rangeof channel-selective disturbance sources, such as channel crosstalk,ripple from optical amplifiers, conversion of phase noise into amplitudenoise on filter flanks, as well as other disturbance possibilities, sothat the evaluation of a monitoring signal transmitted in a singlechannel need not necessarily provide reliable information about thetransmission quality of the optical network. A further limitation to thevalidity of this method results from the fact that the monitoringchannel is terminated in each optical switching apparatus by, aso-called cross connect switch, and does not pass through either acoupling network or a frequency converter and, based on the presentlevel of knowledge, the frequency converter in particular has a criticalinfluence on the signal quality.

In the method described in DE 195 04 896, amplitude samples are takenasynchronously with respect to the signal clock, and the central momentsof the sample are calculated from these samples. These are then comparedwith empirically obtained reference values, and a statement relating tothe signal quality is derived from this comparison. The sampleevaluation by means of the moments is a method which is highly suitableprovided the fundamental population on which the sample is based has asingle-mode probability density function. However, this is not the casewith the present problem.

Thus, in transparent optical networks, it is necessary to monitor thequality of the signals transported by the network without having toaccess payload-specific overhead information, since this would destroythe transparency.

SUMMARY OF THE INVENTION

The subject matter of the application is based on the problem ofspecifying a method for monitoring the signal quality in transparentoptical transmission paths, by means of which it is firstly possible tomake absolute statements on the signal quality and, furthermore, whichis more sensitive.

For the subject matter outlined initially, this problem is solved by animprovement of determining at least one maximum of the two maxima justfrom values of the probability density function, which belong to a flankof the maximum which faces away from the other maximum.

The subject matter of the application makes use of the knowledge thatthe form of the function in the ranges s<a and s>b is independent ofsynchronous sampling or asynchronous sampling and provides an absolutestatement about the signal quality and a high sensitivity, takingaccount of the bimodality of the probability density function of theamplitude samples.

The subject matter of the application will be explained in more detailin the following text as an exemplary embodiment and to an extentrequired for understanding, based on the following Figures.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows an arrangement for carrying out the method according to theapplication,

FIG. 2 shows the probability density function of the two states a=logic0 and b=logic 1 of a binary signal, with a asynchronous sampling beingshown by a solid line, and a synchronous sample being shown by a dashedline,

FIG. 3 shows a flowchart for evaluation according to the application ofthe probability density function for an asynchronously sampled binarysignal, and

FIG. 4 shows a flowchart for further evaluation according to theapplication of the probability density function for an asynchronouslysampled binary signal

DESCRIPTION OF THE PREFERRED EMBODIMENTS

In the figures, identical designations denote identical elements.

In FIG. 1, a fiber-optic directional coupler FORK is introduced into theoptical path between an input E and an output A, and a comparativelysmall proportion of the light power is output through this directionalcoupler FORK and is passed to the optical input of an optoelectronictransducer OEW. The optoelectronic transducer OEW, which may alsoinclude a photo current amplifier, passes a corresponding electricaloutput signal to an analog sampler AB, which operates on thesample-and-hold principle, and works at a signal frequency of 10 GHzwith a clock frequency of 100 MHz which is not synchronized to thesignal frequency. Such analog samplers are commercially available, forexample, for sampling oscilloscopes. The input of an analog-digitalconverter ADW having a resolution of 8 bits, corresponding to 256 steps,is connected to the output of the sampler AB. The analog-digitalconverter ADW operates at the same clock frequency as the analog samplerAB and passes 8 bit words to the input of a computer RE in time with the100 MHz clock, and this computer is being set up for statisticalevaluation of such 8-bit words and contains a memory for referencevalues as well as an output device for the histograms HI which areproduced. A precondition for the statistical evaluation in this case isthat the signal to be investigated is intensity-modulated, and istransmitted using NRZ code. The precondition for statisticalindependence of the amplitude samples which are produced results firstlyfrom the asynchronicity between the signal clock frequency and thesampling frequency, and secondly from the comparatively low samplingfrequency, by means of which samples are reliably taken from mutuallyindependent clock periods.

If the amplitude samples si are each taken at the bit center insynchronism with the data clock, this results, for the fundamental basicpopulation, in a probability density function ps(s) as is outlined by adashed line for binary signals in FIG. 2. The two binary states arerepresented by the amplitude values a and b, about which the noisy,actual amplitude values are distributed with the respective standarddeviation sa or sb, respectively. A signal quality parameter Q, of agenerally normal type, can be calculated from this probability density:$\begin{matrix}{Q = \frac{A}{\sigma_{a} + \sigma_{b}}} & (1)\end{matrix}$

In this case, A=b−a is the signal amplitude, and it is generally thata<b, without any limitation to. Since, in a transparent network, theamplitude samples can be taken only asynchronously with respect to thedata clock, the profile shown by a solid line in FIG. 2 is obtained asthe probability density function ps(s) for the basic population on whichthe sample is based. Since amplitude samples which originate from theflank area of the pulses are now also recorded, the density function israised in the range a<s<b and leads to ps(s) no longer being symmetricalabout a and b. However, the shape of the function is maintained in theregions s<a and s>b. This situation is exploited by the method describedhere. In detail, this method comprises the following steps:

(i) Take statistically independent amplitude samples si of the signal N.

(ii) Determine the positions of the local maxima a and b.

(iii) Calculate sa from the p samples for which s≦a:$\sigma_{a} = \sqrt{\frac{1}{p - 1}{\sum\limits_{l = 1}^{p}\left( {s_{1} - a} \right)^{2}}}$

(iv) Calculate sb from the q samples for which si≧b:$\sigma_{c} = \sqrt{\frac{1}{q - 1}{\sum\limits_{i = 1}^{q}\left( {s_{i} - b} \right)^{2}}}$

(v) Calculate Q in accordance with (1) and output it.

FIG. 3 and FIG. 4 each show an exemplary embodiment in the form of aflowchart. With regard to the notation used there, it should be notedthat variables in square brackets should be regarded as indices, that isto say

x _(i) ≡x[i]

The exemplary embodiment in FIG. 3 is based on the production of ahistogram and its subsequent evaluation for the purposes of the methoddescribed above. This is particularly suitable when an A/D converterwith low resolution (8 bits) is used, and the sample size N is verylarge (for example N>10000).

For arrangements for taking samples which operate with high-resolutionA/D converters (>12 bits) and with a moderate sample size, the histogrammethod is too inaccurate. In this case, the exemplary embodiment shownin FIG. 4 is more suitable. No histogram is produced in this case andthe method searches for the two local maxima a and b by estimation ofps(s). The estimate can be obtained, for example, by the method ofestimating the rate from an inhomogeneous Poisson process by means ofJ-tn waiting times as is known from Numerical recipes in Pascal,Numerical analysis, Applications of computer systems by Press WilliamH., pages 507 . . . 509.

I claim:
 1. A method for monitoring signal quality of a signal in atransparent optical transmission path, the method comprising: samplingthe signal asynchronously to obtain amplitude samples, wherein thesignal is sampled at a substantially lower rate than a bit repetitionrate of the signal; determining positions of local maxima (a, b) in aprobability density function (ps(s)) of the amplitude samples for a lowlogic state 0 denoted by “a” and for a high logic statement 1 denoted by“b”; determining a standard deviation (sa, sb) for at least one maximum(a, b) only from values of the probability density function belonging toa flank of the respective maximum facing away from the respective othermaximum; and determining a signal quality parameter Q from thedetermined values.
 2. A method for monitoring signal quality of a signalas claimed in claim 1, wherein, for both maxima (a, b), distributionsare determined only for the flanks facing away from the respective onemaximum (a, b) with respect to the respective other maximum (b, a).
 3. Amethod for monitoring signal quality of a signal as claimed in claim 1,wherein a search for a maximum (a, b) is carried out via an estimatebased on a known method of “estimation of the rate from an inhomogeneousPoisson process by means of J-tn weighting times.”